ISSN 1312-2622

YEAR IX No. 3 / 2011

CONTENTS
E-Serveces and Productivity
Social Behavior Investigation of Intelligent Virtual Agents
Design and Analysis of Fractional ML-DTC Control System
Centralized Neural Identification and Indirect Adaptive I-term Control of Distributed Parameter Bioprocess Plant
Research on Real Aperture Methods for Determining Distance to Objects in a Scene using Defocus Cue

 

E-Serveces and Productivity
O. Martikainen, M. Kulvik, V. Naumov
Key Words:
E-services; productivity; ICT; business process; process modeling; process improvement.
Abstract:
Services are presently recognized as a source of productivity growth and dynamism in the economy. However, in the public sector, these productivity improvements enabled by services are not easy to recognize. On the contrary, negative productivity effects related to Information and Communication Technologies (ICT) investments have been reported. In this paper, we first consider how ICT changes services and how the how the productivity effects of these changes can be evaluated. Then, we analyze two cases, the Finnish Tax Administration and the Helsimki Central University Hospital Stroke Unit, and draw conclusions about the ICT investments and productivity. Finally, we report some findings on how ICT can be used to improve manual work processes. While business process modeling has been applied in organizations for decades, this paper presents a new approach to analyzing process benefits based on the introduction of ICT services on the hospital floor. We analyze and evaluate the benefits already in the planning phase of an ICT project, taking into account the dynamic nature of processes as they are realized in true work flows.

Social Behavior Investigation of Intelligent Virtual Agents
D. Budakova
Key Words:
Intelligent virtual agents (IVA); architecture; social behavior; social scenario; moral emotions; social emotion primary and secondary emotions; needs; rationalities; knowledge; ambivalence; choice; deception.
Abstract:
This paper investigates the social behavior of an intelligent virtual agents (IVA) with PRE-ThINK architecture with the help of typical working student's life scenario modeling. The program system and the PRE-ThINK architecture, adapted for this scenario, are proposed, and their components are considered. The dynamics of the decision making process in problem situations caused by the implementation of this architecture is shown, when mixed emotions arise and the realization of what happened reflects on the agent's temper. IVA's social behavior is shown, during which in the process of communicating with the user the agent expresses learned from experience secondary emotions, which can be either in harmony or in conflict with the realized secondary emotions, resulting both from the agent's generalized condition and the events. The investigated secondary emotions are: relief, confidence, prestige, uncertainty, confirmed fear, disappointment, and also the socially expressed secondary emotions such as refrained sadness, refrained anger, businesslike manners, politemess and authoritativeness. The results show that the users perceive the modeled IVAs as socially functioning persons, recognize their real emotional state and are interested in their problems.

Design and Analysis of Fractional ML-DTC Control System
E. Nikolov, N. Nikolova, V. Trashlieva
Key Words:
Fractional repetitive and dead-time compensation control - configuration; design; analysis and applications; robust stability and performance; robust margins.
Abstract:
One essentially new class of fractional ML-DRC control systems is proposed in the work. It is configured through combinations of strategy repetitive control, dead-time compensation control and fractional control. Repetitive control is an effective strategy for periodic disturbances suppression by filtering their influence into the contorl system, assuming that the period of disturbances is known. The use of fractional dead-time compensators in the systems provides advantages in quality control of industrial plants with a variable delay. The control with fractional operators of integration and differentiation joins the control systems in the class of robust control systems. In the work are given methods, criteria and synthesis algorithms for fractional ML-DTC control systems. Their application and the analysis of quality are examined.

Centralized Neural Identification and Indirect Adaptive I-term Control of Distributed Parameter Bioprocess Plant
I. Baruh, E. Echevarria Salidierna, B. Nenkova
Key Words:
Recurrent neural network model; Levenberg-Marquardt learning; system identification and state estimation; indirect adaptive neural control; distributed parameter anaerobic bioprocess plant.
Abstract:
The paper proposes a Recurrent Neural Network (RNN) topology and a recursive Levenberg-Marquardt (L-M) algorithm of its learning capable to estimate the states and parameters of an anaerobic continuous bioprocess plant in noisy environment. The analytical model of the digestion bioprocess reperesents a distributed parameter system, which is reduced to a lumped system using the orthogonal collocation method, applied in four collocation points. The proposed RNN identifier is incorporated in an indirect adaptive control scheme (sliding mode and optional control) containing also an integral term.The proposed control scheme is applied for real-time identification and control of continuous fixed bad and recirculation tank bioreactor model in five points, taken from the literature, where a fast convergence, noise filtering and low mean squared error of reference tracking were achieved.

Research on Real Aperture Methods for Determining Distance to Objects in a Scene using Defocus Cue
I. Nikolova, M. Karamihalev, G. Zapryanov
Key Words:
Real aperture methods; depth recovery; image processing; computer vision.
Abstract:
This paper deals with the challenging task of acquiring the three coordinates for the point of interest in the field observed by a camera. This problem is known as scene depth recovery. The present work discusses image analysis techniques relying on the depth cues for determining the distance to objects in a scene. Two fundamentally different depth estimation methods, grounded on measuring the degree of image blur and depth map recovery are examined. Both of them are real aperture imaging methods and are based on a limited depth of field of the camera optics. The objective of the present research investigation and conducted experiments is to verify the effectiveness of the evaluation methods in providing reliable depth estimation of real scenes from digital still camera images. For the purposes of the comparative method of analysis, application software and procedure for determining the geometric parameters of the experimental camera, needed in the calculations, are designed and developed.

The John Atanasoff Society of Automatics and Informatics

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